Time series and graph analysis of Ethereum blockchain

Cryptocurrencies have become increasingly popular with investors over the past few years as a means of transaction. It is primarily an investment asset that can benefit from and get significant returns. The risk of investing is not being able to make 100% accurate price predictions. Therefore, a hig...

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Main Author: Wang,Ye
Other Authors: Anwitaman Datta
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/157055
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1570552022-05-08T11:54:19Z Time series and graph analysis of Ethereum blockchain Wang,Ye Anwitaman Datta School of Computer Science and Engineering Anwitaman@ntu.edu.sg Engineering::Computer science and engineering Cryptocurrencies have become increasingly popular with investors over the past few years as a means of transaction. It is primarily an investment asset that can benefit from and get significant returns. The risk of investing is not being able to make 100% accurate price predictions. Therefore, a high-accuracy price forecast is an artifact that every investor yearns for. However, the task is almost impossible to accomplish. Compared with fiat currencies and ordinary stock markets, cryptocurrencies are more volatile, more ups and downs, and more sensitive to the impact of economic factors. Their prices depend on interoperability with blockchain networks, market trends, social sentiment and even other cryptocurrencies. Therefore, traditional mathematical statistics cannot fully cover the complexities of cryptocurrency exchange rates. Researchers have had to turn to advanced machine learning techniques. Ethereum has become one of the most important cryptocurrencies in terms of transaction volume. Given its recent growth, the cryptocurrency community and researchers are interested in understanding the price of Ethereum. In this project, I propose a method for building machine learning models to predict Ethereum prices, achieving up to 96% short-term and long-term prediction accuracy. Using this method of forecasting and predicting, I propose a buying and selling strategy that helps investors decide whether to invest or sell, and when the time is right. Bachelor of Engineering (Computer Science) 2022-05-08T11:54:19Z 2022-05-08T11:54:19Z 2022 Final Year Project (FYP) Wang, Y. (2022). Time series and graph analysis of Ethereum blockchain. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157055 https://hdl.handle.net/10356/157055 en PSCSE20-0065 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Wang,Ye
Time series and graph analysis of Ethereum blockchain
description Cryptocurrencies have become increasingly popular with investors over the past few years as a means of transaction. It is primarily an investment asset that can benefit from and get significant returns. The risk of investing is not being able to make 100% accurate price predictions. Therefore, a high-accuracy price forecast is an artifact that every investor yearns for. However, the task is almost impossible to accomplish. Compared with fiat currencies and ordinary stock markets, cryptocurrencies are more volatile, more ups and downs, and more sensitive to the impact of economic factors. Their prices depend on interoperability with blockchain networks, market trends, social sentiment and even other cryptocurrencies. Therefore, traditional mathematical statistics cannot fully cover the complexities of cryptocurrency exchange rates. Researchers have had to turn to advanced machine learning techniques. Ethereum has become one of the most important cryptocurrencies in terms of transaction volume. Given its recent growth, the cryptocurrency community and researchers are interested in understanding the price of Ethereum. In this project, I propose a method for building machine learning models to predict Ethereum prices, achieving up to 96% short-term and long-term prediction accuracy. Using this method of forecasting and predicting, I propose a buying and selling strategy that helps investors decide whether to invest or sell, and when the time is right.
author2 Anwitaman Datta
author_facet Anwitaman Datta
Wang,Ye
format Final Year Project
author Wang,Ye
author_sort Wang,Ye
title Time series and graph analysis of Ethereum blockchain
title_short Time series and graph analysis of Ethereum blockchain
title_full Time series and graph analysis of Ethereum blockchain
title_fullStr Time series and graph analysis of Ethereum blockchain
title_full_unstemmed Time series and graph analysis of Ethereum blockchain
title_sort time series and graph analysis of ethereum blockchain
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157055
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